I want to copy the data from a cv::Mat to an std::vector. I could obviously go through the entire Mat and copy each value one by one, but I was hoping that there might be an easier way using copyTo, clone, or some sort of pointer manipulation.
Does anyone have any insight on this problem?
Thanks
Assuming your Mat is CV_8UC1, you can do following.
cv::Mat mat(nrows,ncols,CV_8UC1);
...
std::vector<unsigned char> vec;
vec.assign(mat.data,mat.data+nrows*ncols);
For multiple channel image with different pixel type, I think you will be able to easily generalize the code above.
Here is what worked for myself. I had Mat matVec2f of size Nx1, type Vec2f, and a vector of size N. The following code copies the Mat's data to the vector. I believe this should work equally well for data types other than Vec2f.
int N = 10;
vector<Point2f> vec(N);
matVec2f.copyTo(Mat(vec, false));
Related
When I am trying to read image from file, then after load Mat.Data array is alway null. But when I am looking into Mat object during debug there is byte array in which are all data from image.
Mat image1 = CvInvoke.Imread("minion.bmp", Emgu.CV.CvEnum.LoadImageType.AnyDepth);
Do you have any idea why?
I recognize this question is super old, but I hit the same issue and I suspect the answer lies in the Emgu wiki. Specifically:
Accessing the pixels from Mat
Unlike the Image<,> class, where memory are pre-allocated and fixed, the memory of Mat can be automatically re-allocated by Open CV function calls. We cannot > pre-allocate managed memory and assume the same memory are used through the life time of the Mat object. As a result, Mat class do not contains a Data > property like the Image<,> class, where the pixels can be access through a managed array. To access the data of the Mat, there are a few possible choices.
The easy way and safe way that cost an additional memory copy
The first option is to copy the Mat to an Image<,> object using the Mat.ToImage function. e.g.
Image<Bgr, Byte> img = mat.ToImage<Bgr, Byte>();
The pixel data can then be accessed using the Image<,>.Data property.
You can also convert the Mat to an Matrix<> object. Assuming the Mat contains 8-bit data,
Matrix<Byte> matrix = new Matrix<Byte>(mat.Rows, mat.Cols, mat.NumberOfChannels);
mat.CopyTo(matrix);
Note that you should create Matrix<> with a matching type to the Mat object. If the Mat contains 32-bit floating point value, you should replace Matrix in the above code with Matrix. The pixel data can then be accessed using the Matrix<>.Data property.
The fastest way with no memory copy required. Be caution!!!
The second option is a little bit tricky, but will provide the best performance. This will usually require you to know the size of the Mat object before it is created. So you can allocate managed data array, and create the Mat object by forcing it to use the pinned managed memory. e.g.
//load your 3 channel bgr image here
Mat m1 = ...;
//3 channel bgr image data, if it is single channel, the size should be m1.Width * m1.Height
byte[] data = new byte[m1.Width * m1.Height * 3];`
GCHandle handle = GCHandle.Alloc(data, GCHandleType.Pinned);`
using (Mat m2 = new Mat(m1.Size, DepthType.Cv8U, 3, handle.AddrOfPinnedObject(), m1.Width * 3))`
CvInvoke.BitwiseNot(m1, m2);`
handle.Free();
At this point the data array contains the pixel data of the inverted image. Note that if the Mat m2 was allocated with the wrong size, data[] array will contains all 0s, and no exception will be thrown. So be really careful when performing the above operations.
TL;DR: You can't use the Data object in the way you're hoping to (as of version 3.2 at least). You must copy it to another object which allows use of the Data object.
I used CPU version as follows.
vector<float> descriptors;
cv::HOGDescriptor hog(cv::Size(24,32),cv::Size(12,12),cv::Size(4,4),cv::Size(6,6),6);
hog.compute(img, descriptors,cv::Size(8,8), cv::Size(0,0));
My questions is how can get the 'descriptors' using GPU?
I tried the following code. (doesn't work)
cv::gpu::GpuMat gpu_value, gpu_descriptors;
cv::gpu::HOGDescriptor hog_gpu(Size(24,32),Size(12,12),Size(4,4),Size(6,6),6);
gpu_value.upload(img);
hog_gpu.getDescriptors(gpu_value,cv::Size(8,8),gpu_descriptors);
how can I get the 'descriptors' from 'gpu_descriptors'?
Any one can help me to solve this? Many thanks!
You can download gpu_descriptors to CPU memory using gpu::GpuMat memeber function download(), as follows:
Mat cpu_descriptors;
gpu_descriptors.download(cpu_descriptors);
However, the descriptors may be stored differently on the GPU than on CPU, that is cpu_descriptors may not be exactly the same as descriptors computed in your code above. But you can give it a try.
Edit
There doesn't seem to be a method to download descriptors to CPU memory in vector<float> format for gpu::HOGDescriptor. As a side note, I know that you can download descriptors for gpu::SURF_GPU feature detector, using it's member function
void downloadDescriptors(const GpuMat& descriptorsGPU,
vector<float>& descriptors);
which is exactly what you want. But, unfortunately, for some reason this function doesn't exist for cv::gpu::HOGDescriptor. You can attempt to figure out how the data is stored in vector<float> type of descriptors and then try to convert from Mat to vector<float> format.
I have no idea for how to implement matrix implementation efficiently in OpenCV.
I have binary Mat nz(150,600) with 0 and 1 elements.
I have Mat mk(150,600) with double values.
I like to implement as in Matlab as
sk = mk(nz);
That command copy mk to sk only for those element of mk element at the location where nz has 1. Then make sk into a row matrix.
How can I implement it in OpenCV efficiently for speed and memory?
You should take a look at Mat::copyTo and Mat::clone.
copyTo will make an copy with optional mask where its non-zero elements indicate which matrix elements need to be copied.
mk.copyTo(sk, nz);
And if you really want a row matrix then call sk.reshape() as member sansuiso already suggested. This method ...
creates alternative matrix header for the same data, with different
number of channels and/or different number of rows.
bkausbk gave the best answer. However, a second way around:
A=bitwise_and(nz,mk);
If you access A, you can copy the non-zero into a std::vector. If you want your output to be a cv::Mat instance then you have to allocate the memory first:
S=countNonZero(A); //size of the final output matrix
Now, fast element access is an actual topic of itself. Google it. Or have a look at opencv/modules/core/src/stat.cpp where countNonZero() is implemented to get some ideas.
There are two steps involved in your task.
First, you convert to double the input matrix:
cv::Mat binaryMat; // source matrix, filled somewhere
cv::Mat doubleMat; // target matrix (with doubles)
binaryMat.convertTo(doubleMat, CV64F); // Perform the conversion
Then, reshape the result as a row matrix:
doubleMat = cv::reshape(doubleMat, 1, 1);
// Alternatively:
cv::Mat doubleRow = cv::reshape(doubleMat, 1, 1);
The cv::reshape operation is efficient in the sense that the data is not copied, only the structure header changes.
This function returns a new reference to a matrix (by creating a new header), thus you should not forget to assign its result.
I tried to cv::bitwise_not to a cv::Mat matrix of double values. I applied like
cv::bitwise_not(img, imgtemp);
img is CV_64F data of 0 and 1. But imgtemp has all nonsense data inside.
I am expecting 0 in img to be 1 at imgtemp and 1 in img to be 0 at imgtemp. How to apply bitwise_not to a double Mat matrix?
Thanks
I cannot get the sense of doing a bitwise not of a double (floating point) value: you will be doing bitwise operations also on the exponent (see here). All bits will be inverted, from 0 to 1 and viceversa.
There is also a note on this aspect in the function documentation.
In case of a floating-point input array, its machine-specific bit
representation (usually IEEE754-compliant) is used for the operation.
If you want zeros to become ones and viceversa, as you suggested, you could do:
cv::threshold(warpmask, warpmaskTemp,0.5,1.0,THRESH_BINARY_INV)
(see documentation) (and yes, you can use same matrix for input and destination).
I think you are either getting the method signature wrong or wrongly named the parameters for the bitwise_not method.
According to [OpenCV 2.4.6 Documentation on bitwise_not() method] (http://docs.opencv.org/modules/core/doc/operations_on_arrays.html#void bitwise_not(InputArray src, OutputArray dst, InputArray mask))
void bitwise_not(InputArray src, OutputArray dst, InputArray mask=noArray())
If you are going to use any mask, it needs to be the last argument as mask is an optional for 'bitwise_not' method.
Additionally, all the data types need to be the same in order to avoid confusion. What I am trying to imply is that your source and destination data formats and any interim ones such as the method parameters must be in the same format. You cannot have on ein CV_64F and others in different. If I am not loosing my marbles here, bitwise operation would possibly require you to have all the data in unsigned or signed integer format for the sake of simplicity. Nevertheless, you should have all the types same.
About the garbage that you got, I think it is a general and good programming practice that you initialise your variables with some reasonable values. This helps when you are debugging step by step and ascertain the details where it failed.
Give it a try.
To follow on from Antonio's answer, you should use the right tool for the job. double is not an appropriate storage medium for boolean data.
In open cv you can type a boolean as an unsigned char (8bits). Although in typing your own true value you can pick any non-zero value, in open cv it is more natural to have 0/255; that way fitting in with open cv's bitwise operations and comparison operators. E.g. a bitwise not could be achieved by result = (input == 0) which can take any type. threshold in Antonio's answer maintains the same type (useful in some circumstances). For bitwise_not you should have it in the boolean format first.
Unfortunately opencv makes it very difficult to work with black and white bitwise data.
I am building an image processing application using OpenCV. I am also using the Armadillo library because it has some very neat matrix related functions. The thing is though, in order to use Armadillo functions on cv::Mat I need frequent conversions from cv::Mat to arma::Mat .
To accomplish this I convert the cv::Mat to an arma::Mat using a function like this
arma::Mat cvMat2armaMat(cv::Mat M)
{
copy cv::Mat data to a arma::Mat
return arma::Mat
}
Is there a more efficient way of doing this?
To avoid or reduce copying, you can access the memory used by Armadillo matrices via the .memptr() member function. For example:
mat X(5,6);
double* mem = X.memptr();
Be careful when using the above, as you're not allowed to free the memory yourself (Armadillo will still manage the memory).
Alternatively, you can construct an Armadillo matrix directly from existing memory. For example:
double* data = new double[4*5];
// ... fill data ...
mat X(data, 4, 5, false); // 'false' indicates that no copying is to be done; see docs
In this case you will be responsible for manually managing the memory.
Also bear in mind that Armadillo stores and accesses matrices in column-major order, ie. column 0 is first stored, then column 1, column 2, etc. This is the same as used by MATLAB, LAPACK and BLAS.